Malaria remains a major health problem worldwide. According to the World Health Organization in 2008 there were approximately 850,000 deaths related to malaria, with over 89% occurring in Africa. The tragedy is that technologies exist that can prevent, diagnose and even cure malaria. Preventative technologies that have been shown to be effective in clinical trials include the use of insecticide-treated mosquito nets (ITNs), intermittent preventive treatment during pregnancy (IPT) and prompt and effective treatment of malaria using artemisinin combination therapy (ACT). Despite the fact that most people in Sub-Saharan Africa are aware of the existence of these technologies, a large number of individuals do not adopt them. ITNs, IPT, and ACT are relatively new and their benefits may not be widely evident to the general population because individuals need to continuously experience these technologies to ascertain their effectiveness. When facing choices under uncertainty, individuals have incentives to learn from the actions and outcomes of their neighbors. The action of neighbors may also create peer pressure to engage in certain behaviors. The objective of this study is to determine the importance of these social interactions in the adoption and spread of ITNs, IPT, and ACT using data from all the Demographic Health Surveys (DHS), Malaria Indicator Surveys (MIS), and Multiple Indicator Cluster Surveys (MICS) between 1999 and 2010 for 34 Sub- Saharan countries. For each country we have multiple waves with information on ownership and usage of mosquito nets and ITN, usage of IPT and usage of ACT. Social interactions create a social spillover, where the effect of a government policy that encourages some individuals to adopt these technologies will also have an indirect effect through the influence of these individuals on the behavior of their neighbors. If social interactions are important, small changes in the determinants of malaria-preventative behaviors may lead to a high variation at the aggregate level. It is well known that the problems of identifying social interactions from other phenomena (that give rise to similar outcomes among peers) are immense. This study calculates the size of the social spillover by comparing the effects of an exogenous variable on the malaria preventive behavior at both the individual and group level, defining a group as a region or district of a country. In the presence of social spillovers, the ratio of these two effects will be significantly greater than one, implying that a social policy that convinces a small group of influential people to adopt the technology could have large effects at the community level.